Relational Clustering with Discrete Spatial Structure

In this paper we propose a novel spatial clustering method, named CORSO, that resorts to a relational approach to mine relational data describing the structure that is naturally embedded in spatial data. However, differently from existing relational clustering methods, CORSO is able to mine not only relational data describing spatial data, but also relational constraints forming the discrete spatial structure on the objects to be clustered. An application to real-world spatial data is reported